Contact Tracing Involving An Index Case, Based On Comparing Geo-Temporal Patterns That Include Mobility Profiles

ABSTRACT

A method for performing contact tracing. An analysis system performing the method receives geo-temporal data comprising location data points for various wireless terminals, including the wireless terminals being used by people diagnosed as having a specified disease and the wireless terminals of others, one of whom having possibly infected those diagnosed with the disease. Based on filtering the geo-temporal data, the analysis system generates relatively-condensed mobility profiles that are representative of each person&#39;s locations and movements, and analyzes the mobility profiles. Through careful selections of various parameters based on the disease that is being analyzed, the mobility profiles are used instead of the relatively large amounts of geo-temporal data, to represent users of wireless terminals and to determine their interactions in regard to disease transmission.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of:

-   (i) U.S. Provisional Application Ser. No. 63/007,492, filed Apr. 9,    2020 (Attorney Docket 0465-470pr1), and-   (ii) U.S. Provisional Application Ser. No. 63/007,674, filed Apr. 9,    2020 (Attorney Docket 0465-471pr1), and-   (iii) U.S. Provisional Application Ser. No. 63/007,679, filed Apr.    9, 2020 (Attorney Docket 0465-472pr1),    all of which are incorporated by reference. If there are any    contradictions or inconsistencies in language between this    application and any document that has been incorporated by reference    that might affect the interpretation of the claims in this    application, the claims in this application should be interpreted to    be consistent with the language in this application.

This application is related to “Contact Tracing Based On ComparingGeo-Temporal Patterns Of Wireless Terminals, Including MobilityProfiles,” U.S. application Ser. No. 17/214,840, Attorney Docket465-470us1, filed on Mar. 27, 2021 and incorporated by reference herein.

FIELD OF THE INVENTION

The present invention relates to medicine in general, and, moreparticularly, to the control of infectious diseases.

BACKGROUND OF THE INVENTION

There are some diseases that a person can develop because of thepresence or absence of specific sequences in the person's genome. Also,there are some diseases that a person can develop because ofenvironmental factors in the person's presence.

In contrast, there are some diseases that a person can develop only whenthey come into contact, directly or indirectly, with a person whoalready has the disease. These infectious diseases include measles,smallpox, and coronavirus disease 2019, or “COVID-19.” The path topreventing infectious diseases includes:

-   -   i. the elimination of the source of the pathogen causing the        disease, and    -   ii. the development of vaccines, and    -   iii. the development of herd immunity, and    -   iv. social distancing, and    -   v. identifying and quarantining those people who are infected to        prevent them from infecting others, and    -   vi. identifying and isolating those people who have come into        contact—directly or indirectly—with a person who is already        infected so as to prevent the further spread of the disease.

The process of identifying those people who have, or might have, comeinto contact, directly or indirectly, with an infected entity is called“contact tracing.” Because the modern world comprises inexpensive andwidely-used modes of local- and long-distance transportation, andbecause people regularly come into proximity with many people, theprocess of contact tracing is very difficult.

Some contact tracing methods involve the use of software applications,or “apps,” executing on wireless terminals such as smartphones, whichoperate within a telecommunications network. FIG. 1 depicts a diagram ofthe salient components of telecommunications system 100, in the priorart. Telecommunications system 100 comprises: wireless terminals 101,102, and 103, cellular base stations 104-1, 104-2, and 104-3, Wi-Fi basestations 105-1 and 105-2, wireless switching system 111, and locationsystem 112. Telecommunications system 100 provides wirelesstelecommunications service to all wireless terminals within its coveragearea.

Data that is generated by system 100 can suggest to an investigator(e.g., an epidemiologist, etc.) which:

-   -   i. persons or persons might have had contact with an infected or        infectious person, or    -   ii. animals (e.g., cats, ferrets, bats, etc.) that might have        had contact with an infected or infectious person, or    -   iii. stationary objects (e.g., door knobs, countertop, etc.)        might have been in the vicinity of an infected or infectious        person, or    -   iv. mobile objects (e.g., cars, trucks, trains, airplanes,        bicycles, etc.) might have conveyed an infected or infectious        person, or    -   v. geographic locations where an infected or infection person        might have been, or    -   vi. any combination of i, ii, iii, iv, and v.

For example, an infected entity's geo-location history can be retrievedfrom location system 112 and, once a contact is identified, thecontact's geo-location history can also be retrieved.

Contacts can be identified conventionally by asking about the infectedentity's activities and the activities and roles of the people aroundthem since onset of illness. Contacts can be anyone who has been incontact with an infected entity: family members, work colleagues,friends, health care providers, and others. All persons considered tohave contact with the infected entity should be listed as contacts.However, relying on knowing the infected entity's activities and theactivities and roles of the people around them since onset of illness isflawed. This is because it often relies on the infected entity'srecollection, which is imperfect or incomplete.

Digital contact tracing apps that execute on a smartphone attempt toidentify possible exposures to an infected entity. When the app isenabled to provide exposure notifications, the phone begins usingBluetooth (or another short-range communications protocol) to scanconstantly for nearby phones that are using the same app and doing thesame thing. When two phones connect with each other, they exchangeidentity codes, which are typically anonymous for privacy reasons. Aphone records how long its user spends around the other phone andestimates how far away the other phone is. It does so based on a numberof factors such as the strength of signals received from the otherphone. If the user tests positive for a disease, other people who havebeen exposed to the infected entity can be notified, based on theidentity codes exchanged.

In some ways, using a contact tracing app to track the infected entity'scontact with other people who are also using the same app can be animprovement over relying merely on the infected entity's recollection.However, there are still disadvantages in relying on such an app. A keydisadvantage is requiring a sufficient number of people within apopulation to be using an app that, at a minimum, must be able to detectan exposure and notify either its user or the appropriate healthauthority.

SUMMARY OF THE INVENTION

The present invention enables the control of infectious diseases,without at least some of the disadvantages in the prior art. Anetwork-centric, geo-temporal analysis system disclosed herein receivesgeo-temporal data comprising location data points for various wirelessterminals, including the wireless terminals being used by peoplediagnosed as having a specified disease and the wireless terminals ofothers, one of whom possibly having infected those diagnosed with thedisease. Based on filtering the geo-temporal data, the analysis systemgenerates mobility profiles that are representative of each person'slocations and movements, including a first mobility profile for a firstwireless terminal, a second mobility profile for a second wirelessterminal, and a third mobility profile for a third wireless terminal.For example, the first wireless terminal can be that of a candidateindex case, and the second and third wireless terminals can be those ofpeople who are infected with the disease. In some scenarios regardingthe users of the second and third terminals, they have definitely, or atleast probably, not transmitted the disease to each other, as they havenot crossed or abutted each other's path within a given timeframe, asreflected in their geo-temporal data.

A “mobility profile” can be regarded as a correlation of geographiczones to time periods for a wireless terminal. Each of the geographiczones is an aggregation of location data points, in which there are morelocation data points than there are zones and each data point is capableof representing an infinite number of possible geolocations, in terms oflatitude, longitude, and/or elevation. Accordingly, generating the firstmobility profile comprises defining a first profile time interval thatcomprises a first plurality of time periods, followed by aggregating,over the first profile time interval, selections of the location datafor the first wireless terminal into corresponding zones in a secondplurality of zones.

The first profile time interval, the time periods, and the zones aredefinable by one or more attributes, wherein the one or more attributesare based on characteristics of a disease that the second user isdiagnosed as having. Such characteristics include (i) when an infectedperson is contagious, (ii) the mode(s) of transmission, (iii) thesurface lifespan or stability of a pathogen, and (iv) the persistence ofthe pathogen, for example and without limitation.

The geo-temporal analysis system generates the second mobility profilein a similar way, by defining a second profile time interval thatcomprises a third plurality of time periods, then by aggregating, overthe second profile time interval, selections of the location data forthe second wireless terminal into corresponding zones in a fourthplurality of zones. The analysis system then compares the first mobilityprofile and the second mobility profile, resulting in a first comparisonresult. The analysis system generates an indication of contact based onthe first comparison result exceeding a threshold that indicates arelative likelihood that the first and second user have come intocontact with each other.

Similarly, the geo-temporal analysis system generates the third mobilityprofile for the user of the third wireless terminal and compares thefirst mobility profile and the third mobility profile, resulting in asecond comparison result. The analysis system can generate an indicationof contact based on the second comparison result exceeding a thresholdthat indicates a relative likelihood that the first and third user havecome into contact with each other. Additionally, the analysis system cangenerate an indication of contact based on the combined results ofmultiple comparisons of mobility profiles, adding further evidence thatthe first user is the index case in regard to having exposed the secondand third user to the pathogen causing the disease.

Contact tracing through the use of mobility profiles can provide afaster way of determining whether a first user of a first wirelessterminal has infected a second user of a second wireless terminal and athird user of a third wireless terminal, who have been diagnosed with aparticular disease. The geo-temporal analysis system of the illustrativeembodiment generates and compares the relatively-condensed mobilityprofiles, through careful selections of profile time interval, timeperiods within each profile time interval, and geographic zones thatcorrelate to the time periods, wherein the selections are based on thedisease that is being analyzed. Advantageously, the mobility profilesare compared instead of the relatively large amounts of geo-temporaldata in order to represent the users of the wireless terminals and todetermine their interactions in regard to disease transmission.Moreover, the mobility profiles can be used for contact tracing even inthe absence of any digital contact tracing app being available.

A first method for determining whether a first user of a first wirelessterminal is an index case of a first disease, comprises: receivinglocation data for the first wireless terminal; generating a firstmobility profile for the first wireless terminal, a second mobilityprofile for a second wireless terminal used by a second user, and athird mobility profile for a third wireless terminal used by a thirduser, wherein the generating of the first mobility profile comprises:(i) defining a first profile time interval that comprises a firstplurality of time periods, the first profile time interval being definedby a first attribute, wherein the first attribute is based on a firstdisease that both the second user and the third user are diagnosed ashaving, (ii) aggregating, over the first profile time interval,selections of the location data for the first wireless terminal intocorresponding zones in a second plurality of zones, and (iii) relatingthe zones in the second plurality to corresponding time periods in thefirst plurality; comparing the first mobility profile and the secondmobility profile, resulting in a first comparison result; comparing thefirst mobility profile and the third mobility profile, resulting in asecond comparison result; and generating an indication of contact basedat least one of (i) the first comparison result and (ii) the secondcomparison result exceeding a first threshold that indicates a relativelikelihood that the first user has come into contact with at least oneof (i) the second user and (ii) the third user, respectively.

A second method for determining whether a first user of a first wirelessterminal is an index case of a first disease, comprises: receivinglocation data for the first wireless terminal; generating a firstmobility profile for the first wireless terminal, a second mobilityprofile for a second wireless terminal used by a second user, and athird mobility profile for a third wireless terminal used by a thirduser, wherein the generating of the first mobility profile comprises:(i) defining a first profile time interval that comprises a firstplurality of time periods, the first profile time interval being definedby a first point in time and a second point in time, wherein the firstpoint in time is based on when symptoms of a first disease appear forthe second user, and wherein the second point in time is based on whensymptoms of a first disease appear for the third user, (ii) aggregating,over the first profile time interval, selections of the location datafor the first wireless terminal into corresponding zones in a secondplurality of zones, and (iii) relating the zones in the second pluralityto corresponding time periods in the first plurality; comparing thefirst mobility profile and the second mobility profile, resulting in afirst comparison result; comparing the first mobility profile and thethird mobility profile, resulting in a second comparison result; andgenerating an indication of contact based on a first combination of (i)the first comparison result and (ii) the second comparison resultexceeding a threshold that indicates a relative likelihood that thefirst user has come into contact with both (i) the second user and (ii)the third user.

A third method for determining whether a first user of a first wirelessterminal is an index case of a first disease, comprises: receivinglocation data for the first wireless terminal; generating a firstmobility profile for the first wireless terminal, a second mobilityprofile for a second wireless terminal used by a second user, and athird mobility profile for a third wireless terminal used by a thirduser, wherein the generating of the first mobility profile comprises:(i) defining a first profile time interval that comprises a firstplurality of time periods, the first profile time interval being definedby a first point in time and a second point in time, wherein the firstpoint in time is based on when symptoms of a first disease appear forthe second user, wherein the second point in time is based on whensymptoms of a first disease appear for the third user, and wherein thelength of at least one of the time periods in the first plurality oftime periods is based on a mode of transmission of the first disease,(ii) aggregating, over the first profile time interval, selections ofthe location data for the first wireless terminal into correspondingzones in a second plurality of zones, and (iii) relating the zones inthe second plurality to corresponding time periods in the firstplurality; comparing the first mobility profile and the second mobilityprofile, resulting in a first comparison result; comparing the firstmobility profile and the third mobility profile, resulting in a secondcomparison result; and generating an indication of contact based atleast one of (i) the first comparison result and (ii) the secondcomparison result exceeding a first threshold that indicates a relativelikelihood that the first user has come into contact with at least oneof (i) the second user and (ii) the third user, respectively.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a diagram of the salient components of telecommunicationssystem 100, in the prior art.

FIG. 2 depicts a diagram of the salient components of wirelesstelecommunications system 200 in accordance with the illustrativeembodiment.

FIG. 3 depicts a block diagram of the salient components of geo-temporalanalysis system 213.

FIG. 4 depicts a flowchart of the salient operations of method 400according to the illustrative embodiment.

FIG. 5 depicts a flowchart of the salient sub-operations of operation401.

FIG. 6 depicts a flowchart of the salient sub-operations of operation403.

FIGS. 7A, 7B, and 7C depict mobility profiles 701, 702, and 703,respectively.

FIG. 8 depicts a flowchart of the salient sub-operations of operation405.

FIG. 9 depicts various examples of contact having occurred or contactpossibly having occurred, between two or more persons.

FIG. 10 depicts a flowchart of the salient sub-operations of operation407.

DEFINITIONS

Based on—For the purposes of this specification, the term “based on” isdefined as “being dependent on” in contrast to “being independent of”.The value of Y is dependent on the value of X when the value of Y isdifferent for two or more values of X. The value of Y is independent ofthe value of X when the value of Y is the same for all values of X.Being “based on” includes both functions and relations.

Contact—For the purposes of this specification, the term “contact” andits inflected forms is defined as a person, animal, stationary object,mobile object, or geographic location that might have acquired apathogen from an infected entity.

Contact Tracing—For the purposes of this specification, the term“contact tracing” is defined as the process of identifying the contactswho might have come into contact with an infected entity and subsequentcollection of further information about these contacts.

Generate—For the purposes of this specification, the infinitive “togenerate” and its inflected forms (e.g., “generating”, “generation”,etc.) should be given the ordinary and customary meaning that the termswould have to a person of ordinary skill in the art at the time of theinvention.

Geo-Temporal Attribute—For the purposes of this specification, the term“geo-temporal attribute” is defined as a characteristic that isassociated, or can be associated, with a wireless terminal and comprises(i) a datum that indicates a location, and (ii) a temporal datum thatcorresponds to the location, e.g., timestamp, a point in time, a periodof time, a duration, etc. A geo-temporal attribute can be based on oneor more records of geo-temporal data. Examples of geo-temporalattributes are provided elsewhere herein.

Geo-Temporal Data—For the purposes of this specification, the term“geo-temporal data,” or “spatiotemporal data” within a geographiccontext, is defined as data that comprises (i) a datum that indicates alocation (e.g., of a wireless terminal, etc.), and (ii) a temporal datumthat corresponds to the location, e.g., a timestamp, a point in time, aperiod of time, a duration, etc. Data that indicates locations is“location data.”

Geo-Temporal Pattern—For the purposes of this specification, the term“geo-temporal pattern” is a representation of movement of a wirelessterminal—and, by association, the wireless terminal's user orsubscriber—among one or more locations as a function of time. It isdefined by a composite of attributes of a wireless terminal, includingat least one geo-temporal attribute. A geo-temporal pattern might alsobe defined by other attributes, such as the type of wireless terminal,or certain kinds of calls associated with the wireless terminal atcertain locations and/or times, or the data (if any) transmitted betweenthe wireless terminal and a different wireless terminal at certainlocations and/or times. A geo-temporal pattern typically reflectsattribute data that was gathered over an extended period of time, e.g.,minutes, hours, days, weeks, months, etc. but is not so limited.Examples of a geo-temporal pattern are provided elsewhere herein andinclude, but are not limited to, a subscriber mobility profile, asubscriber behavior model, one or more clusters, one or more records ofgeo-temporal data.

Incubation Period—For the purposes of this specification, the term“incubation period” is defined as the period between exposure to aninfection and the appearance of the first symptoms.

Infected Entity—For the purposes of this specification, the term“infected entity” is defined as the process of identification of aperson who is infected, or is suspected of being infected, with apredetermined disease or diseases. An infected entity is sometimesreferred to as the “index case,” in the context of the index (as the“infecting person”) first bringing a disease into a group of people.

Location—For the purposes of this specification, the term “location” isdefined as a zero-dimensional point, a finite one-dimensional pathsegment, a finite two-dimensional surface area, or a finitethree-dimensional volume. Thus, a location can be described, forexample, by a street address, geographic coordinates, a perimeter, ageofence, a cell ID, or an enhanced cell ID.

Mobility Profile—For the purposes of this specification, the term“mobility profile” is defined as a correlation of geographic zones totime periods for a wireless terminal, wherein the geographic zones areaggregations of locations.

Mode of Transmission—For the purposes of this specification, the term“mode of transmission” is defined as the means by which a pathogencausing communicable disease is passed from an infected host or group toa particular individual or group.

Processor—For the purposes of this specification, a “processor” isdefined as hardware or hardware and software that performs mathematicaland/or logical operations.

Radio—For the purposes of this specification, a “radio” is defined ashardware or hardware and software that is capable of telecommunicationsvia an unguided (i.e., wireless) radio signal of frequency less than 600GHz.

Receive—For the purposes of this specification, the infinitive “toreceive” and its inflected forms (e.g., “receiving”, “received”, etc.)should be given the ordinary and customary meaning that the terms wouldhave to a person of ordinary skill in the art at the time of theinvention.

Transmit—For the purposes of this specification, the infinitive “totransmit” and its inflected forms (e.g., “transmitting”, “transmitted”,etc.) should be given the ordinary and customary meaning that the termswould have to a person of ordinary skill in the art at the time of theinvention.

Wireless Terminal—For the purposes of this specification, the term“wireless terminal” is defined as a device that is capable oftelecommunications without a wire or tangible medium. A wirelessterminal can be mobile or immobile. A wireless terminal can transmit orreceive or transmit and receive. A wireless terminal is also commonlycalled a smartphone, a cellular telephone (“cellphone”), a wirelesstransmit/receive unit (WTRU), a user equipment (UE), a mobile station,wireless handset, a fixed or mobile subscriber unit, a pager, a personaldigital assistant (PDA), an Internet of Things (IoT) device, a computer,or any other type of device capable of operating in a wirelessenvironment are examples of wireless terminals.

DETAILED DESCRIPTION

FIG. 2 depicts a diagram of the salient components of wirelesstelecommunications system 200 in accordance with the illustrativeembodiment of the present invention. System 200 comprises: wirelessterminals 201, 202, and 203, cellular base stations 204-1, 204-2, and204-3, Wi-Fi base stations 205-1 and 205-2, wireless switching system211, location system 212, geo-temporal analysis system 213, GlobalPositioning System (GPS) constellation 221, location system 212,geo-temporal analysis system 213, and data store 214, which areinterrelated as shown.

Wireless telecommunications system 200 provides wirelesstelecommunications service to all wireless terminals within its coveragearea; in addition, geo-temporal analysis system 213 performs andcoordinates the operations as described in more detail below. Externalsystems can also be connected to geo-temporal analysis system 213 viatelecommunications network 230 but are not expressly depicted in FIG. 2,e.g., a facial recognition system, a GPS tracking system, a creditreporting system, a roadway-traffic camera system, a roadway toll-boothsystem, etc., without limitation.

Wireless switching system 211, location system 212, analysis system 213,data store 214, cellular base station 204-1, 204-2, and 204-3, Wi-Fibase stations 205-1 and 205-2, telecommunications network 230, andcommerce system 235 are all connected to one or more interconnectedcomputer networks (e.g., the Internet, a local-area network, a wide-areanetwork, etc.) and, as such, can exchange data.

Wireless terminals 201, 202 and 203 are devices that are capable ofproviding bi-directional voice, data, and video telecommunicationsservices to their respective users, who are also known as “subscribers.”Each wireless terminal comprises the hardware and software necessary toperform the tasks disclosed herein. Furthermore, each wireless terminalis mobile and can be at any location within a geographic region at anytime.

Wireless terminal 201, 202 and 203 can perform at least some of theprocesses described below and in the accompanying figures. For exampleand without limitation, wireless terminal 201, 202 and 203 are capableof:

-   -   i. receiving one or more radio signals transmitted by cellular        base stations 204-1, 204-2, and 204-3, Wi-Fi base stations 205-1        and 205-2, and GPS constellation 121, and    -   ii. identifying each radio signal transmitted by cellular base        stations 204-1, 204-2, and 204-3, Wi-Fi base stations 205-1 and        205-2, and GPS constellation 221, and of transmitting the        identities of those signals, or information related to the        identity of those signals, to location system 212, and    -   iii. measuring one or more location-dependent traits of each        radio signal transmitted by cellular base stations 204-1, 204-2,        and 204-3, Wi-Fi base stations 205-1 and 205-2, and GPS        constellation 221, and of transmitting the measurements to        location system 212, and    -   iv. estimating lateral location x-y and elevation z, based on        one or more of the received and/or measured radio signals, and    -   v. measuring the temperature and barometric pressure at wireless        terminal 201 and transmitting those measurements to location        system 212, and    -   vi. exchanging signals (e.g., Bluetooth, etc.) with one other,        and    -   vii. transmitting one or more signals to cellular base stations        204-1, 204-2, and 204-3, Wi-Fi base stations 205-1 and 205-2 in        accordance with specific parameters (e.g., signal strength,        frequency, coding, modulation, etc.), and of transmitting those        parameters and estimated location to location system 212, and    -   viii. transmitting one or more signals to cellular base stations        204-1, 204-2, and 204-3, Wi-Fi base stations 205-1 and 205-2,        including reports of telecommunications events experienced by        the respective wireless terminal.

Illustrative examples of telecommunications events that are experiencedand reported by wireless terminals 201, 202, and 203 include withoutlimitation:

-   -   i. an origination of a voice call by the wireless terminal,    -   ii. a receiving of a voice call by the wireless terminal,    -   iii. an establishment of a voice call between the wireless        terminal in the wireless network and another telecommunications        terminal, whether in the network or elsewhere, i.e.,        establishing a call connection,    -   iv. an origination of a Short Message Service (“SMS”) message by        the wireless terminal,    -   v. a receiving of an SMS message by the wireless terminal,    -   vi. an origination of a text message by the wireless terminal,    -   vii. a receiving of a text message by the wireless terminal,    -   viii. a location update request that is transmitted by the        wireless terminal to an element of the network infrastructure,    -   ix. an origination by the wireless terminal of an Unstructured        Supplementary Service Data (“USSD”) session,    -   x. an origination of a data session by the wireless terminal,    -   xi. an ending of a data session by the wireless terminal,    -   xii. an activation, for the wireless terminal, of a packet data        protocol (“PDP”) context by a GPRS Support Node in the wireless        network,    -   xiii. a deactivation, for the wireless terminal, of a packet        data protocol (“PDP”) context by a GPRS Support Node in the        wireless network,    -   xiv. the wireless terminal attaching to a packet radio data        network in the wireless network, and    -   xv. the wireless terminal detaching from the packet radio data        network in the wireless network.        Telecommunications-event records are generated (as described        below) that report on the above-listed telecommunications        events, wherein each record also comprises geo-temporal data        associated with the telecommunications event. It will be clear        to those having ordinary skill in the art how to recognize and        implement the corresponding terms, if any, for non-3GPP types of        wireless networks.

Wireless terminal 201, 202 and 203 provide the aforementionedtelecommunications services to their respective users and perform theaforementioned tasks. It will, however, be clear to those skilled in theart, after reading this disclosure, how to make and use embodiments ofthe present invention in which wireless terminal 201, 202 and/or 203provide a different set of services or perform a different set of tasks.

Wireless telecommunications service is provided to wireless terminals201, 202, and 203 in accordance with both the Long-Term Evolution (LTE)4G air-interface standard of the 3^(rd) Generation Partnership Project(“3GPP”) and the WiFi standard. After reading this disclosure, however,it will be clear to those skilled in the art how to make and usealternative embodiments of the present invention that operate inaccordance with one or more other air-interface standards (e.g., a 5Gstandard, a standard under development, a different 4G standard, GlobalSystem Mobile “GSM,” UMTS, CDMA-2000, IS-136 TDMA, IS-95 CDMA, 3GWideband CDMA, other IEEE 802.11 or wireless LAN standard, 802.16 WiMax,Bluetooth, etc.) in one or more frequency bands.

Wireless terminals 201, 202, and 203 receive precise location data fromone or more satellites in GPS constellation 221. As those who areskilled in the art will appreciate after reading this specification,wireless terminal 201, 202 and/or 203 can use technologies other thanGPS for location purposes in some other embodiments of the presentinvention. As those who are skilled in the art will also appreciateafter reading this specification, wireless terminal 201, 202 and/or 203can use a Global Navigation Satellite System (GNSS) other than GPS forlocation purposes, such as GLONASS, Galileo, Beidou, and other regionalsystems, for example and without limitation.

Although the illustrative embodiment depicts wireless telecommunicationssystem 200 as comprising three wireless terminals, it will be clear tothose skilled in the art, after reading this disclosure, how to make anduse alternative embodiments of the present invention that comprise anynumber of wireless terminals.

Cellular base stations 204-1, 204-2, and 204-3 comprise the hardware andsoftware necessary to be Long-Term Evolution (LTE) 3GPP-compliant and toperform the processes described below and in the accompanying figures.In some alternative embodiments of the present invention, base stations204-1, 204-2, and 204-3 communicate in accordance with a differentcellular standard. Each of cellular base stations 204-1, 204-2, and204-3 are capable of continually, for example and without limitation:

-   -   i. receiving one or more radio signals transmitted by wireless        terminals 201, 202, and 203, and    -   ii. identifying each radio signal transmitted by wireless        terminal 201, 202, and 203, and of transmitting the identities        of those signals to location system 212, and    -   iii. measuring one or more location-dependent traits of each        radio signal transmitted by wireless terminal 201, 202, and 203,        and of transmitting the measurements to location system 212, and    -   iv. detecting and reporting on one or more of the        telecommunications events occurring at wireless terminals 201,        202, and 203, and    -   v. transmitting one or more signals to wireless terminal 201,        202, and 203 in accordance with specific parameters (e.g.,        signal strength, frequency, coding, modulation, etc.), and of        transmitting those parameters to location system 212, and    -   vi. broadcasting one or more signals that wireless terminals can        use for various purposes (e.g., mobile assisted handoff,        location determination, etc.).

Wi-Fi base stations 205-1 and 205-2 communicate with wireless terminal201, 202, and 203 via radio and in accordance with a WiFi protocol.Wi-Fi base stations are also commonly referred to by a variety ofalternative names such as access points, nodes, network interfaces, andso forth. In some alternative embodiments of the present invention, basestations 205-1 and 205-2 communicate in accordance with a different IEEE802.11 standard or wireless LAN standard entirely. Wi-Fi base stations205-1 and 205-2 are terrestrial, immobile, and within a geographicregion. Although the illustrative embodiment comprises two Wi-Fi basestations, it will be clear to those skilled in the art, after readingthis disclosure, how to make and use alternative embodiments of thepresent invention that comprise any number of Wi-Fi base stations.

Each of Wi-Fi base stations 205-1 and 205-2 are capable of continually:

-   -   i. receiving one or more radio signals transmitted by wireless        terminal 201, 202, and 203, and    -   ii. identifying each radio signal transmitted by wireless        terminal 201, 202, and 203, and of transmitting the identities        of those signals to location system 212, and    -   iii. measuring one or more location-dependent traits of each        radio signal transmitted by wireless terminal 201, 202, and 203,        and of transmitting the measurements to location system 212, and    -   iv. detecting and reporting on one or more of the        telecommunications events occurring at wireless terminals 201,        202, and 203, and    -   v. transmitting one or more signals to wireless terminals 201,        202, and 203 in accordance with specific parameters (e.g.,        signal strength, frequency, coding, modulation, etc.), and of        transmitting those parameters to location system 212, and    -   vi. broadcasting one or more signals that wireless terminals can        use for various purposes (e.g., mobile assisted handoff,        location determination, etc.).

Wireless switching system 211 comprises a switch that orchestrates theprovisioning of telecommunications service to wireless terminals 201,202, and 203 and the flow of information to and from location system212, and geo-temporal analysis system 213, and data store 214, asdescribed below and in the accompanying figures. As is known to thoseskilled in the art, wireless switches are also commonly referred to byother names such as wireless switching centers, mobile switchingcenters, mobile telephone switching offices, routers, and so on.

Wireless switching system 211 collects data from throughout wirelesstelecommunications system 200, including telecommunications eventsreports that are reported by wireless terminals and/or by base stations,and generates telecommunications-event records according to thetelecommunications events that are listed above, without limitation.Illustratively, wireless switching system 211 collects location datafrom location system 212, from the base stations, and from wirelessterminals 201, 202, and 203. Each telecommunications-event recordgenerated by wireless switching system 211 associates the reported-ontelecommunications event with a geo-temporal datum that indicates alocation and time at which the reported-on telecommunications event isestimated to have occurred. Wireless switching system 211 transmits thetelecommunications-event records to geo-temporal analysis system 213 andto data store 214.

It will be clear to those having ordinary skill in the art, afterreading this disclosure, how to make alternative embodiments whereinwireless switching system 211 is not the entity that generates thetelecommunications-event records, and instead location system 212generates these records; or location system 212 generates these recordsbased at least in part on data gathered from probes; or a combination ofsystem 211-generated and system 212-generated records; or thetelecommunications-event records are generated by another system whetherpart of or outside of system 200, and are made available to geo-temporalanalysis system 213 for processing and analysis as described in furtherdetail below.

Location system 212 comprises hardware and software that estimates oneor more locations for wireless terminals 201, 202, and 203, or maintainsthe location estimates if provided from somewhere else, such as thewireless terminals. Location system 212 provides geo-temporal data thatis to be incorporated into telecommunications-event records, and furtherprovides real-time geo-temporal data on demand, e.g., when geo-temporalanalysis system 213 so requests. The location system estimates alocation that is associated with telecommunications events, includingevents other than call origination and call termination—events such aslocation area updates, powering on, powering off, etc. Location system212 provides location capabilities across 2G (GSM/CDMA), 3G(UMTS/WCDMA), 4G (LTE), and 5G air interfaces, as well as indoortechnologies such as Wi-Fi, DAS, and Femtocells. The location systemenables the ability to simultaneously locate all subscribers in awireless network in real-time and on a historical basis.

Geo-temporal analysis system 213 is a data-processing system thatcomprises hardware and software, and that is configured to perform thegeo-temporal analysis according to the illustrative embodiment,including the generating of subscriber mobility profiles for one or moreof wireless terminals 201, 202, and 203 based on location data obtainedfrom location system 212. Geo-temporal analysis system 213 executes andcoordinates the operations described herein in reference to method 400,including wherein geo-temporal analysis system 213 communicates withexternal systems that are not part of system 200.

Data store 214 is a digital data storage system that is responsible forreceiving, storing, archiving, and retrieving data. Illustratively, datastore 214 receives the results of the analysis performed by geo-temporalanalysis system 213 and archives these results along with the variousrecords and data received by geo-temporal analysis system 213.

Telecommunications network 230 is well known in the art and providesconnectivity and telecommunications (voice and/or data) among thesystems that connect to it, including geo-temporal analysis system 213,one or more commerce systems 235, and systems that are external towireless telecommunications system 200 but are not shown in FIG. 2,e.g., a facial recognition system, a GPS tracking system, a creditreporting system, a roadway-traffic camera system, a roadway toll-boothsystem, etc., without limitation.

Commerce system 235 is well known in the art and is illustratively abanking system that telecommunicates with geo-temporal analysis system213 (illustratively via telecommunications network 230) to transmitfinancial records to geo-temporal analysis system 213, including bankaccount transactions, credit card transactions, debit card transactions,deposits, debits, transfers of funds, and other records that associate auser and/or a wireless terminal with these transactions; the recordsalso preferably comprise geo-temporal data for the reported-ontransactions.

It will be clear to those having ordinary skill in the art, afterreading the present disclosure, how to make and use alternativeembodiments wherein geo-temporal analysis system 213 is incorporatedinto one of the other illustrated systems, e.g., location system 212, orwireless switching system 211. It will be further clear to those havingordinary skill in the art, after reading the present disclosure, how tomake and use alternative embodiments wherein geo-temporal analysissystem 213 further comprises one or more of the other illustratedsystems, e.g., location system 212 and/or wireless switching system 211and/or data store 214. It will be further clear to those having ordinaryskill in the art, after reading the present disclosure, how to make anduse alternative embodiments wherein geo-temporal analysis system 213telecommunicates directly with one or more external systems without theintervening services of telecommunications network 230.

FIG. 3 depicts a block diagram of the salient components of geo-temporalanalysis system 213 in accordance with the illustrative embodiment.Analysis system 213 is a data-processing system that comprises:processor 301, memory 302, and transmitter 303 and receiver 304.

Processor 301 is a general-purpose processor that is well known in theart. Processor 301 can execute an operating system and the applicationsoftware that performs at least some of the operations disclosed herein,including, but not limited to, those in FIG. 4. When operating inconjunction with the other components of analysis system 213, processor301 executes the software, processes data, and telecommunicatesaccording to the operations described herein.

Memory 302 is non-transitory and non-volatile computer memory technologythat is well known in the art. Memory 302 stores operating system 311,application software 312, and element 313 which comprises data, records,results, lists, etc. It will be clear to those having ordinary skill inthe art how to make and use alternative embodiments that comprise morethan one memory 302; or subdivided segments of memory 302; or aplurality of memory technologies that collectively store operatingsystem 311, application software 312, and element 313. The specializedapplication software 312 that is executed by processor 301 isillustratively denominated the “geo-temporal analysis logic” thatenables geo-temporal analysis system 213 to perform the operations ofmethod 400.

Transmitter 303 is a component that enables analysis system 213 totelecommunicate with other components internal and external to wirelesstelecommunications system 200 by transmitting signals thereto. Forexample, transceiver 303 enables telecommunication pathways to wirelessswitching system 211, location system 212, data store 214, etc. withinsystem 200, as well as to other systems that are external to system 200,such as telecommunications network 230, a monitoring system, a trackingsystem, a commerce system, another wireless network, etc., withoutlimitation. Transmitter 303 is well known in the art. It will be clearto those having ordinary skill in the art how to make and usealternative embodiments that comprise more than one transmitter 303.

Receiver 304 is a component that enables analysis system 213 totelecommunicate with other components internal and external to system200 by receiving signals therefrom. For example, receiver 304 enablestelecommunication pathways from wireless switching system 211, locationsystem 212, data store 214, etc. within system 200, as well as fromother systems that are external to system 200, such astelecommunications network 230, a monitoring system, a commerce system,a tracking system, another wireless network, etc., without limitation.Receiver 304 is well known in the art. It will be clear to those havingordinary skill in the art how to make and use alternative embodimentsthat comprise more than one receiver 304.

It will be clear to those skilled in the art, after reading the presentdisclosure, that in alternative embodiments the data-processing hardwareplatform of geo-temporal analysis system 213 can be embodied as amulti-processor platform, as one or more servers, as a sub-component ofa larger computing platform, or in some other computing environment. Itwill be clear to those skilled in the art, after reading the presentdisclosure, how to make and use the data-processing hardware platformfor geo-temporal analysis system 213.

FIG. 4 depicts a flowchart of the salient operations of method 400according to the illustrative embodiment. FIG. 4 and the correspondingtext describe a technique for determining that a first user of a firstwireless terminal has come into contact with a second user of a secondwireless terminal, wherein the second user has been diagnosed with aparticular disease. The figure and corresponding text also describe atechnique for determining whether a first user of a first wirelessterminal is an index case of a disease that both a second user of asecond terminal and a third user of a third terminal are diagnosed ashaving. As those who are skilled in the art will appreciate afterreading the specification, the operations disclosed herein can beadapted for other purposes as well.

Illustratively, the first user is the user of wireless terminal 201, thesecond user is the user of wireless terminal 202, and the third user isthe user of wireless terminal 203, unless otherwise indicated, at leastin the first iteration of the operations described below.Illustratively, the geo-temporal patterns that are generated andcompared are in the form of mobility profiles, unless otherwiseindicated. Illustratively, the mobility profiles that are compared aregenerated as needed and from geo-temporal data, but alternatively can bepredetermined mobility profiles, or other forms of geo-temporalpatterns, which have been generated in advance from geo-temporal data orthrough other means.

Geo-temporal analysis system 213 executes and coordinates the operationsof method 400 in accordance with the illustrative geo-temporal analysislogic. It will be clear to those skilled in the art, after reading thepresent disclosure, how to make and use alternative embodiments of thedisclosed methods wherein some of the disclosed operations are performedby other elements and/or systems. For example and without limitation, atleast some of the operations disclosed as being performed bygeo-temporal analysis system 213 can be performed by one or more oflocation system 212, terminals 201 through 203, and so forth.

It will also be clear to those having ordinary skill in the art, afterreading the present disclosure, how to make and use alternativeembodiments of method 400, and also of any other methods disclosed inthis specification, wherein the recited operations sub-operations, andmessages are differently sequenced, grouped, or sub-divided. It willalso be clear to those skilled in the art, after reading the presentdisclosure, how to make and use alternative embodiments of the disclosedmethods wherein some of the described operations, sub-operations, andmessages are optional, or are omitted.

At operation 401, geo-temporal analysis system 213 receives dataincluding geo-temporal location data records for each wireless terminal201, 202, and 203, and for other wireless terminals. At least some ofthe data, including the location data, are identified by an identifier(e.g., IMSI, etc.) of each wireless terminal. The data includesrecords—of the location data and otherwise—of one or more candidate“contacts” and/or one or more infected persons, who are the users of therespective wireless terminals. Operation 401 is described in more detailin FIG. 5.

At operation 403, geo-temporal analysis system 213 filters the recordsto generate a geo-temporal pattern corresponding to each wirelessterminal, based on one or more characteristics related to a diseasebeing analyzed. In some embodiments of the present invention, acandidate contact's and/or infected person's geo-temporal patterncomprises a subscriber behavioral model of the person—that is, a“subscriber mobility profile” or “mobility profile.” Operation 403 isdescribed in more detail in FIG. 6.

In some embodiments of the present invention, geo-temporal analysis 213initially filters the records to narrow down the wireless terminals tobe analyzed—specifically to the specific wireless terminals for whichgeo-temporal patterns need to be generated. This initial filtering canbe based on one or more characteristics related to the disease beinganalyzed. Insights as to what criteria might be used for this initialfiltering can be found throughout this specification, including in FIG.9. For illustrative purposes, system 213 narrows down the wirelessterminals initially to wireless terminals 201, 202, and 203, althoughadditional candidate wireless terminals can also be processed later(i.e., can take the place of terminal 201 for subsequent iterations ofthe operations described below).

At operation 405, geo-temporal analysis system 213 compares thegeo-temporal patterns of the wireless terminals. In essence, system 213compares the geo-temporal pattern of the candidate contact in thecurrent iteration, with one or more geo-temporal patterns of theinfected person or persons, by comparing the data related to therespective wireless terminals representing their users. Operation 405 isdescribed in more detail in FIG. 8.

At operation 407, based on the comparing of the geo-temporal patterns ofthe wireless terminals at operation 405, geo-temporal analysis system213 infers contact having occurred between the user of the candidatewireless terminal (e.g., the first wireless terminal) and one or moreother users, and generates a corresponding indication of contact.Operation 407 is described in more detail in FIG. 10.

At operation 409, geo-temporal analysis system 213 determines whether torepeat operations 403 through 407 for each additional candidate wirelessterminal, generating that additional candidate's geo-temporal pattern atthe next iteration of operation 403, and comparing that candidatewireless terminal's geo-temporal pattern, at the next iteration ofoperation 405, to that of the second wireless terminal, and to that ofthe first wireless terminal as applicable. For example and withoutlimitation, the users of the additional candidate wireless terminalsmight have been pre-screened as being possible contacts in regard totransmission of the disease being analyzed.

At operation 411, after one or more candidate wireless terminals havebeen analyzed, system 213 ranks the candidate wireless terminals (e.g.,terminal 201, etc.) based on how closely each of their firstgeo-temporal patterns compares to the second, and possibly third,geo-temporal pattern—that is, of wireless terminals 202 and 203—andgenerates a corresponding ranked list of candidates. In accordance withthe illustrative embodiment, a ranking is an assessment of the level ofrisk of infection for each candidate contact associated with a candidatewireless terminal. Depending on what method 400 is being used toanalyze, the level of risk of infection can be in terms of either (i) acandidate wireless terminal's user having been infect by wirelessterminal 202's user, or (ii) a candidate wireless terminal's user beingthe index case in regard to wireless terminal 202's and 203's users.

The ranking scheme can be based on the measures of closeness fromoperation 405 and the threshold checks in operation 407. Differentsensitivity levels can be established in measuring closeness from onecandidate wireless terminal to another (e.g., by applying differentcomparison result thresholds used in operation 407 for the differentcandidate wireless terminals, etc.), thus possibly yielding differentoutcomes in the ranking.

Ranking of one or more candidates can also be determined by the locationitself of where contact has been determined to have occurred, whereincontact at one location, or type of location (e.g., indoor versusoutdoor, immovable versus movable, etc.), might be ranked differentlythan another. The location itself might be immovable (e.g., a room,etc.) or might be movable (e.g., a vehicle, etc.).

At operation 413, and based on the results of operations 407 and/or 411,geo-temporal analysis system 213 transmits (e.g., to location system212, etc.) one or more requests for location estimates of at least oneof the first, second, and third wireless terminals, to one or moreterminals of the ranked contacts, and/or to one or more terminals ofranked contacts above a predetermined ranking, in any combination. Forexample, analysis system 213 transmits a mobile terminated locationrequest (MT-LR), as is known in the art. The location request, and therespective location estimate that is received by geo-temporal analysissystem 213 in response, enable an investigator to begin tracking orsurveilling, for example, the infected person's wireless terminal.

At operation 415, geo-temporal analysis system 213 transmits theindication of contact, the measures of closeness, the set(s) ofcandidate contacts, the ranking of contact candidates, an indication ofthe inferred contact that occurred, and/or any other informationdetermined in one or more of the aforementioned operations in FIG. 4, toa display, to another system, to a wireless terminal, and/or to a datastore, etc., without limitation. Illustratively, geo-temporal analysissystem 213 transmits some or all of the foregoing information to anexternal monitoring system operated by public health authorities, andalso to data store 214.

Geo-temporal analysis system 213 also archives the records and otherdata that formed the basis for operations 401 through 413 to data store214.

FIG. 5 depicts a flowchart of the salient sub-operations of operation401, in which geo-temporal analysis system 213 receives data aboutwireless terminals 201, 202, and 203, including location data.

At operation 501, geo-temporal analysis system 213 receives records thatreport on telecommunications events experienced by wireless terminals201, 202, and 203, described earlier. Each record comprises geo-temporaldata associated with the respective telecommunications event,illustratively a geo-temporal datum documenting the location and pointin time that the telecommunications event is estimated to have occurred(e.g., a record wherein the wireless terminal received a call at alocation L₁ at time T₁, etc.).

Illustratively, these records are generated by and received fromwireless switching system 211, but in alternative embodiments, theserecords are received from another element of system 200, e.g., locationsystem 212, are received from an external system, or are generated bygeo-temporal analysis system 213, or a combination of one or more ofthese sources of records. As noted earlier, any number oftelecommunications events are recorded and reported on in correspondingtelecommunications-event records that are associated with the givenwireless terminal.

At operation 503, geo-temporal analysis system 213 receives records thatreport on other events that are not telecommunications events thatoccurred at the wireless terminal, wherein each record comprisesgeo-temporal data associated with the respective event, illustratively ageo-temporal datum documenting the location and point in time that theevent is estimated to have occurred (e.g., a record wherein the wirelessterminal was used to conduct a financial transaction at a location L₂ attime T₂, e.g., a purchase, a refund, a deposit, a transfer of funds, acredit card transaction, a debit card transaction, etc.).

Illustratively, these records are received from one or more commercesystems 235 and/or from an element of system 200 that provides telecomservice, e.g., a base station, as appropriate. It will be clear to thosehaving ordinary skill in the art, after reading the present disclosure,how to record and report on any number of events, and further how tocollect, construct, generate, and/or receive any number of correspondingnon-telecommunications-event records.

At operation 505, geo-temporal analysis system 213 receives trackingrecords, including associated geo-temporal data (e.g., a record whereinthe wireless terminal was at a location L₃ at time T₃, etc.),corresponding to at least some of the wireless terminals in system 200,e.g., GPS-based and/or other GNSS-based location records of latitude,longitude, and/or elevation, video records, monitoring (e.g.,surveillance, etc.) records, roadway-traffic camera records, toll-boothrecords, etc. without limitation from an appropriate system (e.g.,location system 212, Foursquare, Google, Facebook, etc.).

It will be clear to those having ordinary skill in the art, afterreading the present disclosure, how to record, collect, construct,generate, and/or receive—and process if necessary—the records recited inthe present operation such that each record is associated with aparticular user and/or wireless terminal (e.g., a record that associatesa user's wireless terminal with a pass through a toll booth, a recordthat associates a user's wireless terminal with being in a particularmonitored geographical area, etc.).

At operation 507, geo-temporal analysis system 213 collects data (e.g.,round-trip times, signal strengths, wireless terminal identifiers, typesof messages exchanged, etc.) for electromagnetic signals (e.g., radiosignals, etc.) transmitted between each pair of wireless terminals 201,202, and 203. System 213 also collects or determines time information(e.g., timestamps, etc.) as to when each signal transmission occurred.

At operation 509, geo-temporal analysis system 213 receives data from aGeographic Information System (“GIS”) that is well known in the art,and/or from a similar source of electronic maps. The received datacomprises electronic maps and information about the terrain covered bywireless telecommunications system 200, for example indicating wherethere are water surfaces, parks, streets, buildings, etc. Thisinformation can be correlated to the geo-temporal data to develop,generate, and analyze geo-temporal patterns that comprise usefuladditional attributes, such as indoor/outdoor attributes, etc.

At operation 511, geo-temporal analysis system 213 receives apredetermined geo-temporal pattern of an infected person, such as apredetermined mobility profile. As those who are skilled in the art willappreciate, after reading this specification, a predetermined patterncan be used instead of, or in addition to, one or more patternsgenerated as needed or on-the-fly.

At operation 513, geo-temporal analysis system 213 receives one or morecharacteristics (e.g., epidemiological factors, etc.) about one or morediseases with which the infected person is infected with.

After operation 513, control of task execution proceeds to operation403.

FIG. 6 depicts a flowchart of the salient sub-operations of operation403, in which geo-temporal analysis system 213 generates one or moregeo-temporal patterns, such as mobility profiles.

For each candidate in the set of candidate wireless terminals,geo-temporal analysis system 213 generates a geo-temporal pattern thatis based on data from those records that are associated with therespective candidate contact—and particularly on the geo-temporalattributes gleaned from those records. Depending on the particularimplementation, only some of the records might be selected as the basisfor generating the geo-temporal pattern.

Illustratively, the geo-temporal pattern is generated from analyzing aplurality of records for each candidate, gathered over a period of timesuch as one month, the plurality of records comprising one or more ofthe following without limitation:

-   -   i. records that report on telecommunications events, as received        in operation 501, and    -   ii. records that report on other events that are not        telecommunications events, as received at operation 503, and    -   iii. tracking records, as received in operation 505, and    -   iv. data about the signals exchanged directly between wireless        terminals, as received in operation 507.

Illustrative examples of geo-temporal attributes include one or more ofthe following, alone or in combination, without limitation:

-   -   i. A location and a point in time, e.g., location L₄ at 10 am on        Jul. 11, 2012, and    -   ii. A location and a period of time, e.g., location L₅ from 9:30        to 10:30 am on Jul. 11, 2012, and    -   iii. A location and a duration of time after arrival at that        location, e.g., location L₆ from arrival time until departure        from said location, and    -   iv. A location and a duration of time when no calls are made or        received on the wireless terminal at that location L₇.        It will be clear to those having ordinary skill in the art,        after reading the present disclosure, how to define and use        other geo-temporal attributes upon which a geo-temporal pattern        can be based.

In some alternative embodiments of the present invention, a geo-temporalpattern of an infected person can be received or prepared in advance, inresponse to the person's health practitioner or other health careprovider having contacted the proper health authority, which then hasthe geo-temporal records of the infected person released and/or theidentifier (e.g., IMSI, etc.) of the infected person's wireless terminalor terminals, with which the geo-temporal pattern is created, includingone or more subscriber mobility profiles.

In some embodiments of the present invention, records are filtered basedon the empirical data collected in accordance with operation 507. Forexample, records can be kept based on the degree to which the empiricaldata for electromagnetic signals (e.g., radio signals, etc.) transmittedbetween two wireless terminals suggest that the wireless terminals havebeen proximate to each other, when the wireless terminals have beenproximate, and for how long.

In addition to the records, geographic information—as received inoperation 509—is also available for further analyzing a candidatecontact's records. For example, location data from the records can becorrelated or refined according to the geographic information todetermine whether, for example, a location is known to be outdoors,e.g., a park, a lake, a street, or indoors, e.g., within the footprintof a high-rise building or a warehouse. A level of risk of infection canbe assigned based on whether indoors or outdoors, and/or based on theparticular type of location (e.g., a park, a building, etc.). Forexample, the level of risk can be lower if outdoors and higher ifindoors, if an airborne mode of transmission applies.

Illustrative examples of geo-temporal patterns for a given wirelessterminal include one or more of the following, alone or in anycombination with one other, without limitation:

-   -   i. the set of locations visited by the wireless terminal over a        given period of time, and    -   ii. the set of locations where the wireless terminal spends more        than a certain amount of time, e.g., more than 30 minutes, and    -   iii. the set of locations where the wireless terminal spends a        certain amount of time, e.g., between 15 minutes and 75 minutes,        and    -   iv. the location of the wireless terminal at a certain point in        time, e.g., noon, every weekday, and    -   v. the relative location (e.g., proximity, etc.) of a first        wireless terminal to a second wireless terminal at a certain        point or points in time, and    -   vi. the set of locations where a first wireless terminal is        proximate to a second wireless terminal for more than a certain        amount of time, e.g., more than 30 minutes.

The variety, granularity, periodicity, combinations, and complexity ofgeo-temporal patterns can vary based on the geo-temporal attributesdefining the respective contact tracing. Also, the operative period oftime for determining the geo-temporal pattern also will vary. Thegeo-temporal attributes to be considered in generating a geo-temporalpattern for the candidate contacts' wireless terminals can vary from onecontact tracing to another, and from one wireless terminal and user toanother.

In some embodiments of the present invention, geo-temporal patternsrelated to absolute location in space can be used to infer some types ofinformation, such as a candidate contact's direct exposure to aninfected place, previously visited by an infected person. Geo-temporalpatterns related to location in relation to another wireless terminalcan be used to infer some other types of information, such as acandidate contact's direct exposure to an infected person.

After the proper attributes (e.g., geo-temporal attributes and otherattributes), operational period of time, and other relevantconsiderations are specified for a contact tracing according to theillustrative embodiment, geo-temporal analysis system 213 can usemachine learning techniques that are well known in the art to generatethe geo-temporal pattern for each candidate wireless terminal. It willbe clear to those having ordinary skill in the art, after reading thepresent disclosure, how to make and use alternative embodiments whereinother techniques generate the geo-temporal pattern, or wherein acombination of machine learning and other techniques is used.

In accordance with the illustrative embodiment, geo-temporal analysissystem 213 generates mobility profiles, which comprise a reduced set ofdata points sufficient to profile aspects of the wireless terminal'sbehavior and, with that, the corresponding user's behavior. In oneaspect of the invention, wireless terminal locations collected over aperiod of time, of which there can be an infinite number of possiblelocations, are aggregated into a finite number of geographic zones.

For example, a subscriber (i.e., the wireless terminal user) lives in anapartment complex and works in a nearby office complex. The behaviorpattern for the subscriber is made up of multiple call originations andSMS activity from within the apartment, further activity in theapartment complex common areas, and activity from a car nearby theapartment complex, all of which can be used, along with other recordscollected (e.g., GPS-based, etc.), to determine the subscriber'slocations visited and times at the locations visited. The wirelessterminal exhibits still further activity on the subscriber's workcommute and then activity from different locations within the officecomplex.

In accordance with the illustrative embodiment, this location data isaggregated into a mobility profile where there are two zones, theapartment complex and the office campus, and possibly other zones aswell (e.g., along the commuting route or routes, etc.). The geographicreach of a zone is not limited to a fixed location, nor must each zonecover equal area. According to the present invention, subscribermobility profile zones are aggregated and stored in data store 214accessible to geo-temporal analysis system 213.

Mobile profiles are illustrated in FIGS. 7A, 7B, and 7C, which depictexemplary mobility profiles 701, 702, and 703, respectively, for thesubscribers of wireless terminals 201, 202, and 203. The exemplarymobility profiles span one calendar week of time interval; however, themobility profiles need not coincide with one another in time. Ingeneral, the first profile time interval, second profile time interval,and third profile time interval might or might not overlap with oneother. Further, the profile time interval covered in a given mobilityprofile is configurable.

The exemplary mobility profile time intervals further divide into daysand hours, and consequently provide the subscribers' zone locations in30-minute time periods over the course of week. The length of each timeperiod is configurable and need not be the same as one another. Zones inthis aspect of the invention are an aggregation of higher resolutionlocations that location system 212 may provide. The geographic scope ofa zone is configurable, and the total number of locations considered ina zone aggregation is configurable. The person of ordinary skill in theart after reading this disclosure will know how many locations toconsider in a zone aggregation. In this example, more than 500 locationdata points have been considered for each wireless terminal 201, 202,and 203. Furthermore, the number of data points aggregated into thedifferent zones can vary and might or might not be the same from onezone to another.

Still referring to FIGS. 7A, 7B, and 7C, for any 30-minute time period,mobility profiles 701, 702, and 703 provide the zone location forrespective wireless terminals 201, 202, and 203, if that data isavailable. In other words, it is possible that the wireless terminal wasnot locatable at a certain time, in which case no zone data would beavailable. Or it may be that the wireless terminal was locatable, butthat the system had not aggregated a zone for the more specificlocation. In any case, FIG. 7B illustrates a lack of zone data with ablank for the time period, such as at gaps 708 and 710.

Consider, for example, the TUE column 706. It shows wireless terminal202 located in Zone 6 until 8:00 PM. Between 8:00 AM and 8:30 AM, thereis no zone data available, as denoted by gap 708. From 8:30 AM until atleast 7:00 PM, mobility profile 702 indicates the presence of wirelessterminal 202 in various zones.

Mobility profiles, including how some are generated and used, arefurther discussed in U.S. Pat. No. 10,560,839, which is incorporated byreference herein. In any event, it will be clear to those skilled inart, after reading the present disclosure, how to make and use mobilityprofiles 701, 702, and 703 as part of analysis system 213.

In some embodiments of the present invention, cluster analysis can beused to generate one or more mobility profiles defined by one or moreof: clusters and clustering, uncertainty radius or radii, and entranceand/or exit times. In cluster analysis, for example, high-resolutionlocation data is plotted on a map over a time interval, and the plotsare analyzed for clusters over a predetermined area. A cluster oflocations aggregates to a zone, such as a zone depicted in any of FIGS.7A, 7B, and 7C. The zones may be standardized to shape and geographicarea. Clustering can be used to identify “stay points,” each of whichbeing a separate place (e.g., “home”, “workplace”, etc.) where a person(e.g., an infected person, etc.) spends a significant amount of time asdefined by an identified cluster.

In the example, system 213 can identify the plurality of clusters suchthat the clusters are representative of location of a person and areidentified as a function of time. System 213 can perform a clusteranalysis based on density-based clustering and, in particular, by usingthe data clustering algorithm “DBSCAN” as is known in the art. Clusteranalysis is further discussed in U.S. Pat. Nos. 9,942,713 and10,142,787, both of which are incorporated by reference herein.

In regard to generating a first mobility profile for wireless terminal201, at operation 601 in FIG. 6, geo-temporal analysis system 213defines a first profile time interval that comprises a first pluralityof time periods, such as those referred to above and in regard to FIG.7A. In some embodiments of the present invention, the first profile timeinterval and/or the time periods (e.g., their length or lengths, etc.)in the first profile time interval are defined by one or moreattributes. One or more of the attributes can be based on a firstdisease that a second user is diagnosed as having, for example andwithout limitation. Specific characteristics of the first disease onwhich the one or more attributes can be based are described below.

At operation 603, geo-temporal analysis system 213 aggregates, over thefirst time interval, selections of the location data for the firstwireless terminal into corresponding zones in a second plurality ofzones. In aggregating the selections of the location data, system 213forms or groups higher resolution locations, and possibly an infinitenumber of possible locations, into a finite number of geographic zones.

In some embodiments of the present invention, one or morecharacteristics of the zones (e.g., number of zones, size of each zone,shape of each zone, number of individual locations in a clusteraggregates to a zone, etc.) are defined by one or more attributes. Oneor more of the attributes can be based on a first disease that a seconduser is diagnosed as having, for example and without limitation.Specific characteristics of the first disease on which the one or moreattributes can be based are described below.

At operation 605, geo-temporal analysis system 213 relates the zones inthe second plurality to corresponding time periods in the firstplurality. In relating the zones to the corresponding time periods,system 213 correlates the zones to times.

In generating a second mobility profile for wireless terminal 202, atoperation 607, geo-temporal analysis system 213 defines a second profiletime interval that comprises a third plurality of time periods, such asthose referred to above and in regard to FIG. 7B. The first and secondprofile time intervals might or might not overlap each other. In someembodiments of the present invention, the second profile time intervaland/or the time periods (e.g., their length or lengths, etc.) in thesecond profile time interval are defined by one or more attributes. Oneor more of the attributes can be based on a first disease that a seconduser is diagnosed as having, for example and without limitation.Specific characteristics of the first disease on which the one or moreattributes can be based are described below.

At operation 609, geo-temporal analysis system 213 aggregates, over thesecond time interval, selections of the location data for the secondwireless terminal into corresponding zones in a fourth plurality ofzones. In some embodiments of the present invention, one or morecharacteristics of the zones (e.g., number of zones, size of each zone,shape of each zone, number of individual locations in a clusteraggregates to a zone, etc.) are defined by one or more attributes. Oneor more of the attributes can be based on a first disease that a seconduser is diagnosed as having, for example and without limitation.Specific characteristics of the first disease on which the one or moreattributes can be based are described below.

At operation 611, geo-temporal analysis system 213 relates the zones inthe fourth plurality to corresponding time periods in the thirdplurality.

After operation 611, control of task execution proceeds to operation405.

The operations related to generating a first and second mobility profileare described above. Similar operations can be used to generate a thirdmobility profile for wireless terminal 203 and mobility profiles foradditional wireless terminals. One or more of the attributes used todefine a third mobility profile, and others, can be based on a firstdisease that a second user is diagnosed as having, for example andwithout limitation. Specific characteristics of the first disease onwhich the one or more attributes can be based are described below.

In regard to defining one or more mobility profile time intervals, as inaccordance with operations 601 and 607, one of the relevant geo-temporalattributes might a specified point in time, wherein the point in timecan be used to define a time interval. Accordingly, geo-temporal recordsthat fall outside that time interval can be excluded from the mobilityprofile. The time interval, for example and without limitation, can bedefined by (i) a start time of when the infected person is estimated tohave become contagious and (ii) a stop time, if available, of when theinfected person is estimated no longer to be contagious, wherein thestart time and/or stop time can be adjusted as needed.

The mobility profile time intervals of interest that are described aboveand/or the time periods within each profile time interval and/or thezones, can be based on one or more characteristics of the disease beinganalyzed. For example, a profile time interval can be defined by one ormore epidemiological factors received at operation 513, either alone orin combination with one another. These factors can be used to estimatewhen an infected person first became contagious and, if applicable, whenthe infected person is no longer contagious, wherein the window ofcontagiousness is relevant to defining a profile time interval. When thesymptoms first appeared can be used to determine the start ofcontagiousness based on the particular disease. For example, chickenpoxis infectious from two days before the spots appear. When the symptomsfirst appeared can also be used to determine the end of contagiousnessbased on the particular disease. For example, chickenpox is infectiousuntil after the spots have crusted over, usually five days after thespots first appeared.

Similarly, viral load level(s) of a given disease of a person can beused to determine the time window of contagiousness. The viral loadlevel is obtained from when a person is tested for a particular diseaseand is made available for purposes of contact tracing. Likewise, thelevel of antibodies in the tested person can be used to determinewhether the person has recovered and/or whether the person has beeninfected in the past. Depending on the level of antibodies, along withknowing the particular type of disease involved, other information canbe inferred such as the risk of the previously-infected person beinginfected again and, therefore, contagious again. Thus, it is possiblethat there might be more than one time window during which the infectedperson is contagious, which can affect which profile time interval orintervals are relevant in generating one or more mobility profiles, andwhich are not.

Similarly, the mode or modes of transmission (e.g., airborne, droplet,direct physical contact, indirect physical contact, fecal-oral, etc.) ofa given disease can be used to determine the type of exposure needed inorder for a candidate contact to be infected. The mode or modes oftransmission can also be used to determine the lengths of one or moretime periods in a plurality of time periods defined as part of a profiletime interval. For example, a first mode of transmission might onlyrequire exposure to an infected person for a relatively short amount oftime; accordingly, the length of a time period within a profile timeinterval might need to be decreased (e.g., to 15 minutes, to 5 minutes,etc.) in order to achieve sufficient accuracy when comparing mobilityprofiles. Conversely, a second mode of transmission might requireexposure to an infected person for a relatively long amount of time;accordingly, the length of a time period within a profile time intervalcan be increased (e.g., to 60 minutes, etc.) with negligible or no lossin accuracy when comparing mobility profiles.

The surface lifespan/stability of a pathogen (i.e., a bacterium, virus,or other microorganism that can cause disease) can also be used todetermine the risk of contagion and can be used to define one or moreprofile time intervals and/or the time periods within each profile timeinterval and/or zones. Additionally, the persistence of the pathogen canalso be used to determine the risk of contagion and can be used todefine one or more profile time intervals and/or the time periods withineach profile time interval and/or zones. These characteristics aredescribed in detail below and in regard to FIG. 8.

FIG. 8 depicts a flowchart of the salient sub-operations of operation405, in which geo-temporal analysis system 213 compares the geo-temporalpatterns of the different wireless terminals. This comparison can beaccomplished in various ways, including but not limited to determininghow closely each candidate contact's geo-temporal pattern matches thegeo-temporal pattern of the infected person or persons—that is, howsimilar the patterns are to each other.

A comparison can account for one or more of the followingconsiderations: (i) whether or not the infected person and a candidatecontact were in proximity with each other at a location, (ii) whether ornot the infected person and a candidate contact were at the samelocation as each other, but not necessarily at the same time, (iii) whenthe aforementioned events occurred, either in an absolute sense orrelative to each other, and (iv) the length of time each event occurredfor.

Geo-temporal analysis system 213 measures how closely each candidate'sgeo-temporal pattern matches the geo-temporal pattern of an infectedperson or persons. Geo-temporal analysis system 213 compares onegeo-temporal pattern to another and evaluates a proper measure ofcloseness between them. The measure depends on the nature of thegeo-temporal attributes in the geo-temporal patterns being compared.Some measures can be quantitative and some can be qualitative. Forexample, a first measure can be based on the locations (e.g., the typesof locations, the particular locations, the number of locations) inwhich the infected person and candidate contact have been in proximityto each other. A second measure can be based on the locations that bothinfected person and candidate contact have visited (i.e., locations incommon), but not necessarily at the same time. A third measure can bebased on the length of time that the infected person and candidatecontact are in proximity to each other. A fourth measure can be based onthe length of time that the candidate contact is at a particularlocation previously visited by the infected person.

Additional measures of closeness can be based on: determining whethertwo people (e.g., infected person and candidate contact, etc.) aretraveling together; determining whether two people are in the sameresidential building; determining whether two people are in the sameoffice space; determining whether two people get in and/or out of avehicle (e.g., bus, etc.) at the same place (e.g., bus stop, etc.). Forinstance, if (i) the two people are traveling together and (ii) get inand out of the same vehicle at the same place, then the measure ofcloseness of a match is higher than if (i) they are not travelingtogether or (ii) they get in a vehicle at different places or (iii) theyget out of the vehicle at different places.

Two people traveling together can be inferred by looking either (i) atthe locations and times within each respective geo-temporal pattern or(ii) at one or both geo-temporal patterns to see when a wirelessterminal of the first person transmitted to a wireless terminal of thesecond person. Two people getting in or out of the same vehicle at thesame time can be inferred by respectively comparing (i) when they firstwere proximate to each other to a GIS database (e.g., bus stops, etc.)or (ii) when they stopped being proximate to each other to said GISdatabase.

Additional measures of closeness can be based on assessing proximitybetween the respective first and second wireless terminals, resulting inan assessed proximity. In some embodiments of the present invention,assessed proximity is based, at least in part, on the data collected atoperation 507 for electromagnetic signals transmitted between the firstand second wireless terminals, including time information (e.g.,timestamps, etc.) corresponding to the data for the electromagneticsignals. For example and without limitation, the time or times thatsignals were transmitted directly between two wireless terminals can beused to determine how long two wireless terminals—and, therefore, twousers—were proximate in space to each other. Also, the times can be usedto determine whether the two wireless terminals were proximate in spaceto each other during a time window when an infected person wascontagious.

For example, if the two wireless terminals exchange Bluetooth signals,then the respective users must have come within Bluetooth range of eachother and, consequently, were closer to each other than if the twoterminals were out of Bluetooth range. Generally, the proximity of twowireless terminals—and, correspondingly, of an infected person andcandidate contact—can be gauged based on the range of signal receptionof the technology being used for direct terminal-to-terminalcommunication (i.e., electromagnetic signals directly transmittedbetween two wireless terminals).

As those who are skilled in the art will appreciate, after reading thisspecification, the range of signal reception of other technologies(e.g., WiFi Direct, D2D, near-field communication [NFC], etc.) can beused. For example, In Release 12 in the 3GPP specifications(incorporated by reference herein), ProSe (Proximity Services) is a D2D(Device-to-Device) technology that allows LTE devices to detect eachother and to communicate directly. ProSe relies on multiple enhancementsto existing LTE standards including new functional elements and a“sidelink” air interface for direct connectivity between devices.

The surface lifespan/stability of a pathogen (i.e., a bacterium, virus,or other microorganism that can cause disease) can be used to determinethe risk of contagion and, therefore, can be used as another measure ofcloseness. A particular pathogen might live/persist on a first type ofsurface (e.g., cardboard, etc.) for a first length of time (e.g., 24hours, etc.), while a different pathogen might live/persist on a secondtype of surface (e.g., plastic, etc.) for a second length of time (e.g.,3 days, etc.). In particular, analysis system 213 determines closenessby determining (i) how long after the infected person visited thelocation did the candidate contact visit the same location and (ii)whether the pathogen was still infectious at the time the candidatecontact visited the location.

The surface lifespan/stability of a pathogen at a particular locationcan be assumed (e.g., worst case of 4 days, etc.) or estimated. Analysissystem 213 can estimate the lifespan by estimating the type of surfaceat a location. For example, a parcel distribution center might havepredominantly cardboard surfaces (i.e., on the shipping boxes), while anoffice complex might tend to have hard or shiny surfaces (e.g., metal,plastic, etc.); information about a particular location (e.g., zoning,type of business, etc.) can be found in the GIS or other type ofdatabase. Once the type of surface is estimated, the lifespancorresponding to that type of surface can be cross-referenced.

The persistence of a pathogen can be also related to whether thelocation is indoors or outdoors. For example, an airborne pathogen candissipate more quickly outdoors than indoors. Accordingly, analysissystem 213 can determine closeness in a match between infected personand candidate contact by determining (i) how long after the infectedperson visited the location did the candidate contact visit the samelocation and (ii) whether the pathogen dissipated sufficiently becausethe location was outdoors instead of indoors. Alternatively, aneffective dissipated time can be assigned based on whether the locationis outdoors or indoors. Additionally, the wind conditions can beconsidered if the location is outdoors, and ventilation conditions canbe considered if the location is indoors.

In regard to the persistence of a pathogen within a particularenvironment and location, the time window of the persistence (e.g., asecond time window, etc.) can be managed as a separate time window thanthe time window that an infected person is contagious (e.g., a firsttime window, etc.).

These illustrative examples are presented here for clarity. As noted, aproper measure of closeness depends closely on the nature of therelevant geo-temporal attributes and is specific to the details of thecontact tracing and the data that are available to the geo-temporalanalysis system. For example, the investigator might have informationthat suggests that a known infected person makes one or more visits to aparticular location; if there are multiple, if inaccurate, estimatesthat a candidate contact visited the same location, the superposition ofthese multiple estimates leads toward a higher confidence that theinfected person and candidate contact were at the same location.

In regard to comparing two mobility profiles, FIGS. 7A, 7B, and 7C alsoillustrate mobility profile matching in accordance with the illustrativeembodiment. As per mobility profile 701 in FIG. 7A, on Sunday (“SUN”)wireless terminal 201 remains in the same zone (i.e., Home Zone 1) forthe day. On Monday (“MON”) morning, wireless terminal 201 moves duringits user's commute to Zone 3, then Zone 4, and then Zone 5, arriving atOffice Zone 2 at about 9:30 AM. Wireless terminal 201 remains thereuntil about 3:00 PM, when the wireless terminal's user commutes home toZone 1 via Zones 5, 4, and 3. Mobile profile 701 also includes thelocations and movements of terminal 201 for Tuesday through Saturday aswell. This mobility profile is consistent with a person moving betweentheir home and their place of work during the week, and staying at homeon the weekend.

Meanwhile, wireless terminal 202's mobility profile 702 in FIG. 7Brepresents the wireless terminal's zone locations over the same timeinterval. As per mobility profile 702, on Sunday (“SUN”) wirelessterminal 202 remains in the same zone (i.e., Home Zone 6) for the day.On Monday (“MON”) morning, wireless terminal 202 moves during its user'scommute to Zone 3, then Zone 4, and then Zone 8, arriving at Office Zone7 at about 9:30 AM. Wireless terminal 202 remains there until about 3:30PM, when the wireless terminal's user commutes home to Zone 6 via Zones8, 4, and 3. Mobile profile 702 also includes the locations andmovements of terminal 202 for Tuesday through Saturday as well.

Lastly, wireless terminal 203's mobility profile 703 in FIG. 7Crepresents the wireless terminal's zone locations over the same timeinterval. As per mobility profile 703, on Sunday (“SUN”) wirelessterminal 203 remains in the same zone (i.e., Home Zone 9) for the day.On Monday (“MON”) morning, wireless terminal 203 moves during its user'scommute to Zone 10 and then Zone 11, arriving at Office Zone 2 at about9:30 AM. Wireless terminal 203 remains there until about 5:00 PM, whenthe wireless terminal's user commutes home to Zone 9 via Zones 11 andthen 10. Mobile profile 703 also includes the locations and movements ofterminal 203 for Tuesday through Saturday as well.

In a profile-matching algorithm of the illustrative embodiment, analysissystem 213 totals points based, at least in part, on the number ofmatching zones between the wireless terminals' respective mobilityprofiles. In this exemplary case described above, in terms of the zonesin which their users are both present during the same time periods,mobility profile 701 for terminal 201 and mobility profile 702 forterminal 202 match each other in eight different respective time periods(i.e., between the two profiles) during the week: in Zones 3 and 4 onMonday between 8:00 and 9:00 AM, on Tuesday between 4:00 and 5:00 PM,and on Wednesday and Thursday between 8:00 and 9:00 AM.

Meanwhile, in terms of the zones in which their users are both presentduring the same time periods, mobility profile 701 for terminal 201 andmobility profile 703 for terminal 203 match each other in 60 differentrespective time periods during the week: all in Zone 2 (i.e., the placeof work for both users 1 and 3) on Monday 11 times, on Tuesday 9 times,on Wednesday 15 times, on Thursday 14 times, and on Friday 11 times.

In comparing mobility profiles 702 for terminal 202 of the second userand 703 for terminal 203 of the third user, it can be seen that thereare no zones in which the users are both present during the same timeperiods, nor do the users visit any of the same zones throughout theentire profile time intervals of interest. Thus, if both the second andthird users are infected, it is probably not the case that one infectedthe other. But it is possible that the first user (as the index case)infected both the second and third user, as shown in the analysis thatfollows.

Based on the number of matching zones in which the users are bothpresent during the same time periods, users 1 and 3 have a greaternumber of matches than users 1 and 2, resulting in a larger comparisonresult. Thus, based on matches in same respective time periods alone, itwould appear that user 1 is at greater risk from infected user 3 thanfrom infected user 2, assuming that the purpose of the analysis is toassess user 1's risk of exposure to the disease.

Additionally, the various measures of closeness described earlier can beapplied to the foregoing point-scoring algorithm, in order to generate acomparison result. For example, if the window of contagiousness has notalready been accounted for in defining the mobility profile intervals,the number of matching zones might be less than described above inregard to risk of contagion. Accordingly, the number of matching zonesbetween users 1 and 3 can be reduced because user 3 is not contagiousthroughout the entire week. As another example, the risk of contagion inZone 2 (e.g., a well-ventilated office complex, etc.) might be known inadvance to be less than that somewhere else; accordingly, the number ofmatching zones between users 1 and 3 can be reduced. As yet anotherexample, the surface stability and/or persistence of the pathogen mightbe long enough so that zone matches between time period in a firstprofile and a time period that is offset in a second profile need to beconsidered; accordingly, there are additional matches between users 1and 2 based on their similar, but not identical, commuting patternsthrough Zones 3 then 4 in the morning and Zones 4 then 3 in theafternoon, in which users 1 and 2 are present in some of the same zones,but at slightly different times.

Additionally, the measure of closeness pertaining the wireless terminalexchanging electromagnetic signals described earlier can also be appliedto the foregoing point-scoring algorithm, in order to generate acomparison result. For example, additional points can be applied basedon whether radio signals (e.g., Bluetooth, etc.) are transmitteddirectly between the wireless terminals of interest, within those zonesin which their users are both present during the same time periods, andcan also be based on factors related to the transmissions, such asreceived signal strength and timing.

As those having ordinary skill in the art will appreciate after readingthis specification, the profile-matching algorithm can be configuredwith a different point totaling system. Also, the point valuesassociated with each condition that is met can be selected to suit theparticular purpose of the implementation. Likewise, the mobility profilematching algorithm can be applied to different types of zones, to longeror shorter profile time intervals, and/or to longer or shorter timeperiods.

As part of performing the comparing of mobility profiles 701 and 702 asdescribed above, at operation 801 geo-temporal analysis system 213defines respective time periods between the first plurality of timeperiods for the first wireless terminal and the third plurality of timeperiods for the second wireless terminal. In other words, the individualtime periods whose zones are to be compared across the mobilityprofiles, are defined. The respective time periods might or might notcoincide in absolute time.

At operation 803, geo-temporal analysis system 213, for each of therespective time periods, compares a first zone (e.g., “Zone 1”, “Zone2”, etc.) visited by the first wireless terminal in the second pluralityof zones and a second zone (e.g., “Zone 1”, “Zone 2”, etc.) visited bythe second wireless terminal in the fourth plurality of zones.

At operation 805, geo-temporal analysis system 213 generate a firstcomparison result based, at least in part, on the comparing of the firstand second zones. For example and without limitation, the value of thefirst comparison result might be based on how many matches are found tobe present for all of the respective time periods whose zones arecompared, between the first and second mobility profiles.

The operations related to comparing a first and second mobility profileare described above. Similar operations can be used to compare the firstand/or second mobility profile and a third mobility profile for wirelessterminal 203 (i.e., mobility profile 703). Accordingly, at operation 807geo-temporal analysis system 213 generates a second comparison resultinvolving the first wireless terminal and the third wireless terminal.For example and without limitation, the value of the second comparisonresult might be based on how many matches are found to be present forall of the respective time periods whose zones are compared, between thefirst and third mobility profiles.

After operation 807, control of task execution proceeds to operation407.

FIG. 9 depicts various examples of contact having occurred or contactpossibly having occurred, between two or more persons. The examplesprovide insights into at least some considerations that need to be madein selecting, generating, and comparing the geo-temporal patterns of thewireless terminals. The tracks of various people are shown and labeledas persons A through G, constructed from the geo-temporal datacorresponding to each person's wireless terminal. Direction of tracksare shown by arrowheads. The tracks are determined from the geo-temporaldata of the respective wireless terminals, and can be represented asmobility profiles generated at operation 403, which are then compared toone another at operation 405.

Illustratively, track A is that of an infected person (“person A”),whose wireless terminal's identifier (e.g., an IMSI, etc.) is madeavailable for tracking purposes. Person A becomes infected with apathogen of a particular disease at data point X1, reports firstsymptoms as having occurred around a date and time corresponding to datapoint X2. X1 can be derived from X2 based on the particular disease'sincubation period. Person A is considered to be no longer contagious ata date and time corresponding to data point X3.

For purposes of clarity, the tracks of person A and the others aresimplifications compared to what might be more typical tracks of peoplethroughout a geographic area and during a prolonged interval of time.Accordingly, the positions of data points X1, X2, and X3 have beensimplified compared to where they would be along an actual track of aperson over many days of contagiousness. Similarly, the tracks of otherpersons in relation to person A have also been simplified.

Person B crosses paths (i.e., intersects) with person A's track.However, B is not at risk in regard to A because A is not considered tohave been contagious at the time and place of intersection. Hence, amobility profile—or another type of geo-temporal pattern, for thatmatter—corresponding to B need not be generated or considered.

Person C intersects person A's track, but was at the intersection pointbefore person A was. Thus, person C is not at risk of infection fromperson A, even though A was already infected when A was at theintersection point. Hence, a mobility profile corresponding to C neednot be generated or considered.

Person D intersects person A's track, and was at the intersection pointafter person A was. Thus, person D might be at risk of infection fromperson A. The level of risk depends on various factors describedelsewhere herein, such as the lifespan/persistence of a pathogen of apredetermined disease, for example and without limitation. For example,surface stability is an important consideration, as D might touch asurface on which the pathogen is still present, which might constitute afirst level of risk. Hence, these characteristics are relevant indefining and using a mobility profile corresponding to D, as alreadydescribed.

Person E intersects person A's track, and was at the intersection pointat the same time as A. In other words, A and E were proximate in spaceto each other. Thus, person E might be at risk of infection from personA. The level of risk depends on various factors described elsewhereherein, such as the lifespan/persistence of a pathogen of apredetermined disease and mode of transmission, for example and withoutlimitation. For example, mode of transmission is an importantconsideration, as E might inhale the pathogen when A sneezes, whichmight constitute a second level of risk. Hence, these characteristicsare relevant in defining and using a mobility profile corresponding toE, as already described.

Person F intersects person A's track, and A and F were proximate to eachother, and for a sustained amount of time. Illustratively, F (as trackF1) got on a bus that A was already on and got off the bus later (astrack F2). Thus, person F might be at risk of infection from person A.The level of risk depends on various factors described elsewhere herein,such as the lifespan/persistence of a pathogen of a predetermineddisease and mode of transmission and amount of time exposed to theinfected person or area, for example and without limitation. Forexample, exposure time is an important consideration, as F has moreopportunities for infection if A and F are proximate to each other for aprolonged amount of time, accordingly, this might constitute a thirdlevel of risk. Hence, these characteristics are relevant in defining andusing a mobility profile corresponding to F, as already described.

Person G crosses paths (intersects) with person A's track. However, G isnot at risk in regard to A because A is no longer considered to becontagious at the time and place of intersection. Hence, a mobilityprofile corresponding to G need not be generated or considered.

As those who are skilled in the art will appreciate after reading thisspecification, in some embodiments the various risk levels might beassigned according to a different set of situations than what isrepresented in FIG. 9.

Alternatively, the identities of one or more persons B through G mightbe known before the identity and track of person A. In such analternative scenario, the purpose of an investigation might be todetermine the identity of person A as an infecting person (e.g., anindex case, etc.) responsible for having infected one or more otherpersons (e.g., one or more of persons B through G, etc.). In otherwords, a first person (candidate infecting person) can have infectedboth a second person (infected person) and a third person (infectedperson). In this case, the first person is still a candidate, but interms of how that person (as an index case) might have infected theother two, instead of the first person possibly being infected byanother.

For instance, persons E and F are confirmed to be infected with apathogen. Persons E and F have not crossed each other's paths, so theidentity of a third person needs to be determined. Various candidategeo-temporal patterns can be tried (e.g., those of A, B, C, D, and G)until it is determined that A's geo-temporal pattern has similaritiesthat those of E and F. The candidate geo-temporal patterns that E's andF's geo-temporal patterns are compared against for similarity can beselected based on any of a number of attributes—for example, based on anextrapolation back in time to a range of times during which each of Eand F might be gotten infected (e.g. all possible intersections lastTuesday for E and last Wednesday for F).

In particular, person E intersected with person A at the store, andperson F intersected with person A at work—in this case, the exposure isdirect person-to-person. Or it might be determined that person A toucheda particular object (e.g., a doorknob) or had been at a particular place(e.g., a store) prior to both E and F—in this case, the exposure islocation-based. The infected location might be stationary, as in store,or it might be moving, such as person A having been in a vehicle (e.g.,a taxi) prior to both E and F, which can be determined from thegeo-temporal pattern showing similar movement (e.g., vehicular motion),albeit at different times, along a similar route (e.g., a street).

FIG. 10 depicts a flowchart of the salient sub-operations of operation407, in which geo-temporal analysis system 213 generates an indicationof contact occurring between two or more persons.

At operation 1001, geo-temporal analysis system 213 compares each of thefirst and second comparison results to one or more thresholds. Thespecific values of the one or more thresholds can be determined throughempirical analysis, for example and without limitation.

At operation 1003, geo-temporal analysis system 213 compares a firstcombination of (i) the first comparison result and (ii) the secondcomparison result, to a threshold. The specific value of the thresholdcan be determined through empirical analysis, for example and withoutlimitation.

At operation 1005, geo-temporal analysis system 213 assesses proximityof two or more wireless terminals to one another based on radio signaldata collected at operation 507 for electromagnetic signals transmitteddirectly between the wireless terminals. This results in an assessedproximity, wherein the assessed proximity is based on whether radiosignals, as represented by the radio signal data, are transmittedbetween the wireless terminals of interest within at least one of thetime periods in the plurality of time periods in the profile timeinterval of interest (e.g., the first profile time interval, etc.). Themeasures of closeness related to considering the electromagnetic signalsthat are described above and in regard to operation 405, can beadditionally or alternatively applied here for the purpose of assessingproximity.

In some embodiments of the present invention, the assessed proximity isfurther based on whether the radio signals are transmitted between thewireless terminals of interest within at least N of the time periods inthe applicable plurality of time periods making up the applicableprofile time interval. The value of N can be based on one or moreattributes. One or more of the attributes can be based on a firstdisease that a second user is diagnosed as having, for example andwithout limitation. Specific characteristics of the first disease (e.g.,mode of transmission, etc.) on which the one or more attributes can bebased are described elsewhere in this specification.

At operation 1007, geo-temporal analysis system 213 generates anindication of the inferred contact that occurred, if any, according tothe outcomes of operations 1001 through 1005. Generally speaking, aparameter exceeding a threshold described in operation 1001 and 1003 cantrigger generating of the indication of contact. An assessment ofproximity at operation 1005 can also be probative of contact and caninfluence the indication of contact.

In some embodiments of the present invention, system 212 generates theindication of contact based on the first comparison result at operation1001 exceeding a threshold that indicates a relative likelihood that thefirst user of wireless terminal 201 has come into contact with thesecond user of wireless terminal 202.

In some embodiments of the present invention, system 212 generates theindication of contact based on the second comparison result at operation1001 exceeding a threshold that indicates a relative likelihood that thefirst user of wireless terminal 201 has come into contact with the thirduser of wireless terminal 203.

In some embodiments of the present invention, system 212 generates theindication of contact based on a first combination of (i) the firstcomparison result and (ii) the second comparison result exceeding athreshold that indicates a relative likelihood that the first user hascome into contact with both (i) the second user and (ii) the third user.

In some embodiments of the present invention, system 212 generates theindication of contact is further based on whether both (i) at least onematch is found to be present at operation 803 for all of the respectivetime periods between the first zone and the second zone and (ii) atleast one match of zones visited by the first and third wirelessterminals exists for a given time period.

After operation 1007, control of task execution proceeds to operation409.

It is to be understood that the disclosure teaches just some examplesaccording to illustrative embodiments of the present invention and thatmany variations of the present invention can be devised by those skilledin the art after reading this disclosure. The scope of the presentinvention is to be determined by the following claims.

What is claimed is:
 1. A method for determining whether a first user ofa first wireless terminal is an index case of a first disease, themethod comprising: receiving location data for the first wirelessterminal; generating a first mobility profile for the first wirelessterminal, a second mobility profile for a second wireless terminal usedby a second user, and a third mobility profile for a third wirelessterminal used by a third user, wherein the generating of the firstmobility profile comprises: (i) defining a first profile time intervalthat comprises a first plurality of time periods, the first profile timeinterval being defined by a first attribute, wherein the first attributeis based on a first disease that both the second user and the third userare diagnosed as having, (ii) aggregating, over the first profile timeinterval, selections of the location data for the first wirelessterminal into corresponding zones in a second plurality of zones, and(iii) relating the zones in the second plurality to corresponding timeperiods in the first plurality; comparing the first mobility profile andthe second mobility profile, resulting in a first comparison result;comparing the first mobility profile and the third mobility profile,resulting in a second comparison result; and generating an indication ofcontact based at least one of (i) the first comparison result and (ii)the second comparison result exceeding a first threshold that indicatesa relative likelihood that the first user has come into contact with atleast one of (i) the second user and (ii) the third user, respectively.2. The method of claim 1, further comprising transmitting, based on theindication of contact being generated, at least one of: (i) theindication of contact, and (ii) a request for a location estimate of thefirst wireless terminal.
 3. The method of claim 1, further comprising:receiving location data for the second wireless terminal; wherein thegenerating of the second mobility profile comprises: (i) defining asecond profile time interval that comprises a third plurality of timeperiods, wherein the first profile time interval and the second profiletime interval overlap with each other, (ii) aggregating, over the secondprofile time interval, selections of the location data for the secondwireless terminal into corresponding zones in a fourth plurality ofzones, and (iii) relating the zones in the fourth plurality tocorresponding time periods in the third plurality.
 4. The method ofclaim 3, wherein the comparing of the first mobility profile and thesecond mobility profile comprises: defining respective time periodsbetween the first plurality of time periods and the third plurality oftime periods; and for each of the respective time periods, comparing afirst zone visited by the first wireless terminal in the secondplurality of zones and a second zone visited by the second wirelessterminal in the fourth plurality of zones; wherein a value of the firstcomparison result is based, at least in part, on the comparing of thefirst and second zones.
 5. The method of claim 4, wherein a value of thefirst comparison result is further based, at least, at least in part, onhow many matches of the first zone and the second zone are found to bepresent for all of the respective time periods.
 6. The method of claim4, wherein the indication of contact is further based on whether both(i) at least one match is found to be present for all of the respectivetime periods between the first zone and the second zone and (ii) atleast one match of zones visited by the first and third wirelessterminals exists for a given time period.
 7. The method of claim 3,further comprising relating a first zone in the fourth plurality ofzones to a corresponding first time period in the third plurality oftime periods; wherein the first attribute is a first point in time thatis based on when symptoms of the first disease appear for the seconduser, wherein the first time period comprises the first point in time,and wherein a value of the first comparison result is based, at least inpart, on comparing (i) a first zone in the second plurality of zones forthe first wireless terminal and (ii) a second zone in the fourthplurality of zones for the second wireless terminal.
 8. The method ofclaim 7, wherein the first point in time is further based on whensymptoms of the first disease appear for the third user.
 9. The methodof claim 1, wherein the indication of contact is further based on afirst combination of (i) the first comparison result and (ii) the secondcomparison result exceeding a second threshold that indicates a relativelikelihood that the first user has come into contact with both (i) thesecond user and (ii) the third user.
 10. The method of claim 1, whereinthe length of at least one of the time periods in the first plurality oftime periods is based on a mode of transmission of the first disease.11. A method for determining whether a first user of a first wirelessterminal is an index case of a first disease, the method comprising:receiving location data for the first wireless terminal; generating afirst mobility profile for the first wireless terminal, a secondmobility profile for a second wireless terminal used by a second user,and a third mobility profile for a third wireless terminal used by athird user, wherein the generating of the first mobility profilecomprises: (i) defining a first profile time interval that comprises afirst plurality of time periods, the first profile time interval beingdefined by a first point in time and a second point in time, wherein thefirst point in time is based on when symptoms of a first disease appearfor the second user, and wherein the second point in time is based onwhen symptoms of a first disease appear for the third user, (ii)aggregating, over the first profile time interval, selections of thelocation data for the first wireless terminal into corresponding zonesin a second plurality of zones, and (iii) relating the zones in thesecond plurality to corresponding time periods in the first plurality;comparing the first mobility profile and the second mobility profile,resulting in a first comparison result; comparing the first mobilityprofile and the third mobility profile, resulting in a second comparisonresult; and generating an indication of contact based on a firstcombination of (i) the first comparison result and (ii) the secondcomparison result exceeding a threshold that indicates a relativelikelihood that the first user has come into contact with both (i) thesecond user and (ii) the third user.
 12. The method of claim 11, furthercomprising transmitting, based on the indication of contact beinggenerated, at least one of: (i) the indication of contact, and (ii) arequest for a location estimate of the first wireless terminal.
 13. Themethod of claim 11, further comprising: receiving location data for thesecond wireless terminal; wherein the generating of the second mobilityprofile comprises: (i) defining a second profile time interval thatcomprises a third plurality of time periods, wherein the first profiletime interval and the second profile time interval overlap with eachother, (ii) aggregating, over the second profile time interval,selections of the location data for the second wireless terminal intocorresponding zones in a fourth plurality of zones, and (iii) relatingthe zones in the fourth plurality to corresponding time periods in thethird plurality.
 14. The method of claim 13, wherein the comparing ofthe first mobility profile and the second mobility profile comprises:defining respective time periods between the first plurality of timeperiods and the third plurality of time periods; and for each of therespective time periods, comparing a first zone visited by the firstwireless terminal in the second plurality of zones and a second zonevisited by the second wireless terminal in the fourth plurality ofzones; wherein a value of the first comparison result is based, at leastin part, on the comparing of the first and second zones.
 15. The methodof claim 14, wherein a value of the first comparison result is furtherbased, at least, at least in part, on how many matches of the first zoneand the second zone are found to be present for all of the respectivetime periods.
 16. A method for determining whether a first user of afirst wireless terminal is an index case of a first disease, the methodcomprising: receiving location data for the first wireless terminal;generating a first mobility profile for the first wireless terminal, asecond mobility profile for a second wireless terminal used by a seconduser, and a third mobility profile for a third wireless terminal used bya third user, wherein the generating of the first mobility profilecomprises: (i) defining a first profile time interval that comprises afirst plurality of time periods, the first profile time interval beingdefined by a first point in time and a second point in time, wherein thefirst point in time is based on when symptoms of a first disease appearfor the second user, wherein the second point in time is based on whensymptoms of a first disease appear for the third user, and wherein thelength of at least one of the time periods in the first plurality oftime periods is based on a mode of transmission of the first disease,(ii) aggregating, over the first profile time interval, selections ofthe location data for the first wireless terminal into correspondingzones in a second plurality of zones, and (iii) relating the zones inthe second plurality to corresponding time periods in the firstplurality; comparing the first mobility profile and the second mobilityprofile, resulting in a first comparison result; comparing the firstmobility profile and the third mobility profile, resulting in a secondcomparison result; and generating an indication of contact based atleast one of (i) the first comparison result and (ii) the secondcomparison result exceeding a first threshold that indicates a relativelikelihood that the first user has come into contact with at least oneof (i) the second user and (ii) the third user, respectively.
 17. Themethod of claim 16, further comprising transmitting, based on theindication of contact being generated, at least one of: (i) theindication of contact, and (ii) a request for a location estimate of thefirst wireless terminal.
 18. The method of claim 16, further comprising:receiving location data for the second wireless terminal; wherein thegenerating of the second mobility profile comprises: (i) defining asecond profile time interval that comprises a third plurality of timeperiods, wherein the first profile time interval and the second profiletime interval overlap with each other, (ii) aggregating, over the secondprofile time interval, selections of the location data for the secondwireless terminal into corresponding zones in a fourth plurality ofzones, and (iii) relating the zones in the fourth plurality tocorresponding time periods in the third plurality.
 19. The method ofclaim 18, wherein the comparing of the first mobility profile and thesecond mobility profile comprises: defining respective time periodsbetween the first plurality of time periods and the third plurality oftime periods; and for each of the respective time periods, comparing afirst zone visited by the first wireless terminal in the secondplurality of zones and a second zone visited by the second wirelessterminal in the fourth plurality of zones; wherein a value of the firstcomparison result is based, at least in part, on the comparing of thefirst and second zones.
 20. The method of claim 19, wherein a value ofthe first comparison result is further based, at least, at least inpart, on how many matches of the first zone and the second zone arefound to be present for all of the respective time periods.